Abstract
Background: Acute kidney injury is an adverse event that carries significant morbidity among patients with acute decompensated heart failure (ADHF). We planned to develop a parsimonious model that is simple enough to use in clinical practice to predict the risk of acute kidney injury (AKI) occurrence.Methods: Six hundred and fifty patients with ADHF were enrolled in this study. Data for each patient were collected from medical records. We took three different approaches of variable selection to derive four multivariable logistic regression model. We selected six candidate predictors that led to a relatively stable outcome in different models to derive the final prediction model. The prediction model was verified through the use of the C-Statistics and calibration curve.Results: Acute kidney injury occurred in 42.8% of the patients. Advanced age, diabetes, previous renal dysfunction, high baseline creatinine, high B-type natriuretic peptide, and hypoalbuminemia were the strongest predictors for AKI. The prediction model showed moderate discrimination C-Statistics: 0.766 (95% CI, 0.729–0.803) and good identical calibration.Conclusion: In this study, we developed a prediction model and nomogram to estimate the risk of AKI among patients with ADHF. It may help clinical physicians detect AKI and manage it promptly.
Highlights
Acute kidney injury is an adverse event that carries significant morbidity among patients with acute decompensated heart failure (ADHF)
650 patients with ADHF were enrolled in this study, and 278 had acute kidney injury (AKI), meaning that the incidence of AKI was 42.8%
We developed model A of variable selection by Akaike information criterion (AIC)-based stepwise that consisted of 15 variables
Summary
Acute kidney injury is an adverse event that carries significant morbidity among patients with acute decompensated heart failure (ADHF). We planned to develop a parsimonious model that is simple enough to use in clinical practice to predict the risk of acute kidney injury (AKI) occurrence. In patients with acute decompensated heart failure (ADHF), the incidence and impact of acute kidney injury (AKI) have been reported mainly in subjects hospitalized with acute HF (AHF), in which the prevalence of AKI is about 20% [1]. Detection of patients at higher risk for AKI occurrence would help physicians to plan and initiate appropriate managements to improve the renal safety of therapies, augment surveillance of cardiac and renal dysfunction, and develop renal-preserving treatments. A substantial proportion of cases of AKI are thought to be preventable with early treatment [4, 5]
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